Accessible Data Science for the Blind Using R

Three Available Packages Tailored for Visually Impaired R Users

There are three packages for the blind R users “sonify” (Siegert & Williams, 2017) for data sonification; “BrailleR” for data textualization (Godfrey, Warren, Murrell, Bilton, & Sorge, 2020); and “tactileR” for data tactualization [Seo (2020); ].

Data Sonification

Figure 1: Sample scatter plot.

You can sonify the scatterplot above using “sonify” package (Siegert & Williams, 2017) as follows:

library(sonify)
sonify(1:5, 1:5)

Data Textualization

You can get an alternative text description for some basic R graphs using “BrailleR” package (Godfrey et al., 2020).

Basic R Graph

Histogram

Figure 2: Histogram of Ozone.

Figure 2 can be textualized like below:

library(BrailleR)
VI(hist(airquality$Ozone))

## This is a histogram, with the title: Histogram of airquality$Ozone
## "airquality$Ozone" is marked on the x-axis.
## Tick marks for the x-axis are at: 0, 50, 100, and 150 
## There are a total of 116 elements for this variable.
## Tick marks for the y-axis are at: 0, 10, 20, and 30 
## It has 9 bins with equal widths, starting at 0 and ending at 180 .
## The mids and counts for the bins are:
## mid = 10  count = 37 
## mid = 30  count = 34 
## mid = 50  count = 14 
## mid = 70  count = 15 
## mid = 90  count = 9 
## mid = 110  count = 4 
## mid = 130  count = 2 
## mid = 150  count = 0 
## mid = 170  count = 1

Boxplot

Figure 3: Boxplot of dist.

Figure 3 can be textualized like below:

library(BrailleR)
VI(boxplot(cars$dist))

## This graph has a boxplot printed vertically
## with the title: 
## "" appears on the x-axis.
## "" appears on the y-axis.
## Tick marks for the y-axis are at: 0, 20, 40, 60, 80, 100, and 120 
## This variable 1 has 50 values.
## An outlier is marked at: 120 
## The whiskers extend to 2 and 93 from the ends of the box, 
## which are at 26 and 56 
## The median, 36 is 33 % from the lower end of the box to the upper end.
## The upper whisker is 1.54 times the length of the lower whisker.

Ggplot

Some graphics produced by ggplot2 package (Wickham et al., 2020) can be also textualized.

Figure 4: Population Growth: An Example Line Chart.

The following is the textualized version of the Figure 4:

VI(g)
## This chart has title 'Population Growth'.
## It has x-axis 'Month' with labels .
## It has y-axis 'Population' with labels .
## There is a legend indicating that colour is used to represent factor(year), with 16 levels:
## 2000 represented by colour light greenish blue, 
## 2001 represented by colour dark greenish blue, 
## 2002 represented by colour brilliant blue, 
## 2003 represented by colour very light blue, 
## 2004 represented by colour vivid bluish green, 
## 2005 represented by colour light bluish green, 
## 2006 represented by colour strong reddish brown, 
## 2007 represented by colour strong yellowish pink, 
## 2008 represented by colour light gray, 
## 2009 represented by colour white, 
## 2010 represented by colour white, 
## 2011 represented by colour white, 
## 2012 represented by colour white, 
## 2013 represented by colour white, 
## 2014 represented by colour white and 
## 2015 represented by colour white.
## The chart is a set of 16 lines.

Data Tactualization

You can even make a tactile graph using “tactileR” package (Seo, 2020).

Please refer to the following video that explains how I create a tactile graph.

References

Godfrey, A. J. R., Warren, D., Murrell, P., Bilton, T., & Sorge, V. (2020). BrailleR: Improved access for blind users. Retrieved from https://github.com/ajrgodfrey/BrailleR

Seo, J. (2020). TactileR: Converting r graphics into a braille ready-to-print pdf. Retrieved from https://github.com/jooyoungseo/tactileR

Siegert, S., & Williams, R. (2017). Sonify: Data sonification - turning data into sound. Retrieved from https://CRAN.R-project.org/package=sonify

Wickham, H., Chang, W., Henry, L., Pedersen, T. L., Takahashi, K., Wilke, C., … Dunnington, D. (2020). Ggplot2: Create elegant data visualisations using the grammar of graphics. Retrieved from https://CRAN.R-project.org/package=ggplot2

JooYoung Seo
JooYoung Seo
Ph.D. Candidate (ABD) in Learning, Design, and Technology

My research topics include STEM education, computational thinking and accessible makerspaces.

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